通过心理语言学分析区分AI与人类写作，提升学术诚信检测可信度。
Distinguishing AI-Generated and Human-Written Text Through Psycholinguistic Analysis
- 将31个风格特征映射至认知过程，构建可解释的判别框架。
- 揭示人类写作特有的心理语言模式，如元认知监控与认知负荷管理。
- 适合教育领域、论文查重及生成内容监管场景使用。
随着AI生成文本的日益复杂，准确透明的检测工具在教育场景中愈发重要，以保障作者身份验证的可靠性。现有研究已证明，结合风格特征与机器学习分类器可取得优异效果。本研究在此基础上提出一个整合风格分析与心理语言学理论的综合性框架，提供清晰可解释的区分方法。具体地，将31种风格特征映射至词汇检索、话语规划、认知负荷管理及元认知自我监控等认知过程，揭示人类写作的独特心理语言模式。该框架融合计算语言学与认知科学，助力开发可靠的工具，以维护生成式AI时代的学术诚信。
原文摘要 · Abstract (English)
The increasing sophistication of AI-generated texts highlights the urgent need for accurate and transparent detection tools, especially in educational settings, where verifying authorship is essential. Existing literature has demonstrated that the application of stylometric features with machine learning classifiers can yield excellent results. Building on this foundation, this study proposes a comprehensive framework that integrates stylometric analysis with psycholinguistic theories, offering a clear and interpretable approach to distinguishing between AI-generated and human-written texts. This research specifically maps 31 distinct stylometric features to cognitive processes such as lexical retrieval, discourse planning, cognitive load management, and metacognitive self-monitoring. In doing so, it highlights the unique psycholinguistic patterns found in human writing. Through the intersection of computational linguistics and cognitive science, this framework contributes to the development of reliable tools aimed at preserving academic integrity in the era of generative AI.
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